Field of the Invention
One or more embodiments of the invention are related to the fields of motion analysis and biomechanics. More particularly, but not by way of limitation, one or more embodiments of the invention enable a method that determines the stress on a joint, such as an elbow for example, using sensor data.
Description of the Related Art
Human joints are subject to severe stresses that may lead to fatigue or injury. These stresses and risks are particularly acute in certain sports activities, such as baseball pitching. In baseball, for example, injury to the ulnar collateral ligament (UCL) commonly occurs in pitchers, with an increasing incidence in recent years. The UCL is located on the inside of the (medial) elbow and connects the upper arm (humerus) to a bone in the forearm (ulna). Movement patterns that simultaneously bend and twist the elbow have been shown to place the highest loads on the UCL. Dr. Frank Jobe developed a revolutionary UCL reconstructive surgical technique in 1974 that used a transplanted tendon to replace the damaged UCL. Tommy John was the first player to undergo this procedure, and Jobe's surgical technique is most commonly referred to as Tommy John Surgery (TJS). Due to the high incidence of UCL injuries in pitchers, this injury mechanism is often referred to as the Tommy John (TJ) epidemic.
These injuries result in significant time lost due to the injury itself, surgery if necessary, and the required rehab. In Major League Baseball (MLB), the dollars lost due to contracts on the disabled list (DL) and their replacement costs continue to climb year after year, jumping in 2012 due to a correlative spike in TJ related injuries. A typical rehab time frame from TJS is 12-18 months, with a statistical return to near pre-injury performance levels requiring the longer time frame of approximately 18 months. For a pitcher with a $10 million-dollar annual contract, that is a significant sunk cost. As a result, MLB and MLB teams are investing significant money into analysis of pitching injuries, with the desire to develop more predictive tools for preventing throwing injuries.
While there has been a lot of research performed on overhead throwing athletes over the past 30 years, there has not been much at all in terms of definitive injury mechanisms from these research studies. The American Sports Medicine Institute (ASMI) has performed the majority of these studies using traditional motion capture techniques. Studies to date have focused primarily on the osteokinematics of the throwing motion, which describes gross movements of skeletal bones at the joints produced by active musculotendon forces. However, joint stress is also a function of arthrokinematics, which is the very small movements of skeletal bones at the joint surface produced by passive joint properties as the joint approaches end range of motion. Passive joint stresses due to elastic structures found at a joint, including ligaments, joint capsules, and surrounding soft tissues, provide strong restoring joint moments near a joint's end range of motion. When a joint degree of freedom is isometrically held at end range of motion for some duration of time, active muscle forces are required to counteract these passive joint moments that are trying to move the joint out of the end range of motion, thereby prematurely fatiguing the same musculature that is meant to protect the joint ligaments from excessive loading during high-speed dynamic movements. Premature fatigue of the musculature of the proximal and/or distal segments may result in altered coordination and control patterns and can subject the joint ligaments to a higher percentage of total joint loading on each action (such as each throw), thereby increasing the injury risk for the athlete.
A good example of the difference between osteokinematics and arthrokinematics is to consider knee flexion/extension during sports movements. As an athlete is dynamically moving, active musculotendon forces cause the resultant knee flexion/extension that can be observed through traditional osteokinematic analysis using motion capture data. If at any point, the athlete approaches end range of motion for knee extension to the point of approaching knee hyperextension, it is at this point that we must consider arthrokinematic effects as well. As the human knee approaches full extension, a “screw-home” mechanism is employed which provides inherent knee stability to hopefully prevent catastrophic injury. If the joint continues into end range of motion, a passive joint moment is created which provides a restoring joint moment which acts to push the joint back into the normal range of motion to prevent catastrophic injury
Every human joint has arthrokinematic effects. In reality, it is very difficult to accurately measure arthrokinematics, especially during high-speed athletic movements. As a result, methods known in the art to analyze joint stresses have generally not taken into account arthrokinematic effects. These effects may be modeled by taking into account active and passive joint ranges of motion, since arthrokinematic effects dominate at the end (or outside) of a joint's normal (active) range of motion as the joint transitions from an active range of motion to passive range of motion. This approach to analyzing joint stress is not known in the art. Most performance studies only consider the speed effects on joint stress. For these types of studies, the total or resultant joint stress is only used for analysis. However, when fatigue is an important consideration for dynamic performance and injury risk assessment, modeling steps that account for both active (osteokinematic) and passive (arthrokinematic) joint stress contributions are the only methodology that allows for analyses that can concurrently examine performance and injury risk.
For at least the limitations described above there is a need for a method of determining joint stress from sensor data. Embodiments of this method may for example determine the relative contributions of both active (osteokinematic) and passive (arthrokinematic) forces on total joint stress, using sensor data to determine when a joint exceeds its normal (active) range of motion.